Quantitative structure–activity relationship for the partition coefficient of hydrophobic compounds between silicone oil and air

Abstract

The silicon oil-air partition coefficients (K_SiO/A) of hydrophobic compounds are vital parameters for applying silicone oil as non-aqueous-phase liquid in partitioning bioreactors. Due to the limited number of K_SiO/A values determined by experiment for hydrophobic compounds, there is an urgent need to model the K_SiO/A values for unknown chemicals. In the present study, we developed a universal quantitative structure–activity relationship (QSAR) model using a sequential approach with macro-constitutional and micromolecular descriptors for silicone oil-air partition coefficients (K_SiO/A) of hydrophobic compounds with large structural variance. The geometry optimization and vibrational frequencies of each chemical were calculated using the hybrid density functional theory at the B3LYP/6-311G** level. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates that a regression model derived from logK_SiO/A, the number of non-hydrogen atoms (#nonHatoms) and energy gap of E_LUMO and E_HOMO (E_LUMO–E_HOMO) could explain the partitioning mechanism of hydrophobic compounds between silicone oil and air. The correlation coefficient R² of the model is 0.922, and the internal and external validation coefficient, Q²_LOO and Q²_ext , are 0.91 and 0.89 respectively, implying that the model has satisfactory goodness-of-fit, robustness, and predictive ability and thus provides a robust predictive tool to estimate the logK_SiO/A values for chemicals in application domain. The applicability domain of the model was visualized by the Williams plot.